Abstract:

Objective: To investigate the inconsistency between the fluorescent PCR probe melting curve method (“melting curve method”) and the microplate method in detecting the susceptibility of rifampicin, and to provide an explanation for the inconsistency between clinical genotypic and phenotypic drug susceptability test (pDST) results. Methods: We collected the data of 2562 culture positive tuberculosis patients in Xi’an Chest Hospital from August 2019 to September 2020 and screened out 1294 strains with different results using melting curve method and microplate pDST. The correlation between the inconsistent results and the mutation of rpoB gene were analyzed by sequencing the rpoB gene. Results: Among the 54 patients (4.17%, 54/1294) whose melting curve testing results were inconsistent with the pDST test results, 45 were melting curve method positive for mutants but pDST negative, and 8 were melting curve method negative for mutants but pDST positive. One case was detected as having heterogeneous drug resistance by melting curve method, thus was excluded from the analysis. When the rpoB gene was mutated at codons of 507-512, the inconsistency rate with the pDST results was the highest (70.59%, 24/34), and the minimum inhibitory concentrations of the inconsistent strains tested with the microplate method were mostly ≤1 ug/ml. Leu511pro was the most frequently observed mutation, accounting for 45.28% (24/53), followed by Leu533pro, accounting for 15.09% (8/53) of all of the inconsistent strains. Both Asp516Tyr and His526Asn mutations accounted for 5.66% (3/53). All 8 strains that were melting curve method negative for mutants but pDST positive were sequenced as no mutation in the rpoB gene region. Conclusion: The mutations of Leu511Pro, Leu533Pro, Asp516Tyr and His526Asn in the rpoB region were the main reasons for the inconsistency between the genotypic and phenotypic results for Mycobacterium tuberculosis susceptibility to rifampicin, but whether it was related to the low-level drug resistance mechanism still need further research.

Key words: Mycobacterium tuberculosis, Drug resistance,bacterial, Microbial sensitivity tests, Data interpretation,statistical